Social Network Analysis Research Articles

The rise of syndicates: Social network analyses of construction waste haulers in Hong Kong using a novel InfoMap-XGBoost method

In areas with a low entry barrier, small businesses tend to organize into informal syndicates to survive or thrive. However, there is little empirical evidence to show how these syndicates evolve, and ultimately, impact business and environment. This research investigates syndicates evolving among construction waste haulers in Hong Kong and their broad impacts. It does so by applying a novel social network analysis (SNA) framework named InfoMap-XGBoost to a big data set covering over 10 million payload trips conducted by waste haulers over the past 10 years. Our analyses show that (a) syndicates spontaneously emerge as the whole social network expands by merging with each other; (b) occupying a higher centrality within the syndicate is more significant than joining a larger syndicate in helping actors receive more hauling orders with bigger values; (c) larger and denser syndicates help alleviate adverse environmental impact by improving the overall business efficiency.

Examining Teachers' Professional Relationships, Friendship, and Trust Networks via Social Network Analysis

In this study, Social Network Analysis method was used to determine the professional relationships, friendships and trust networks that teachers established with their colleagues. The study group of the research consists of 35 teachers working in a public secondary education institution in Aydın province. A three-question structured interview form developed by the researchers was used to determine teachers' social networks. Data analysis was carried out through the UCINET 6.0 program. When the findings regarding the positions of teachers in the professional relationship network, friendship network and trust network were examined, it was determined that the network structure with the highest number of connections was the friendship network (ties = 97), followed by the professional relationship (ties = 95) and the trust network (ties = 66). In all social networks, teachers with mathematics, guidance, literature and biology branches were found to be at the center of the network, acting as a bridge between other actors and providing information and resource flow. According to the findings, it was determined that the network with the highest density (dens. = 0.082), bilateral (dia. = 0.198) and triad (triad = 0.330) reciprocity rate was the friendship network. This study, which examines the professional relationships, friendships and trust networks that teachers establish with their colleagues, is thought to be important in revealing the relationships between teachers and analyzing the current situation.

Faculty members as academic knowledge brokers in Iran's health sector: a social network analysis study

BackgroundInteraction between researchers and policymakers is an essential factor to facilitate the evidence-informed policymaking. One of the effective ways to establish this relationship and promote evidence-informed policymaking is to employ people or organizations that can play the role of knowledge brokers. This study aims to analyze the communication network and interactions between researchers and policymakers in Iran's health sector and identify key people serving as academic knowledge brokers.MethodsThis study was a survey research. Using a census approach, we administered a sociometric survey to faculty members in the health field in top ten Iranian medical universities to construct academic-policymaker network using social network analysis method. Network maps were generated using UCINET and NetDraw software. We used Indegree Centrality, Outdegree Centrality, and Betweenness Centrality indicators to determine knowledge brokers in the network.ResultsThe drawn network had a total of 188 nodes consisting of 94 university faculty members and 94 policymakers at three national, provincial, and university levels. The network comprised a total of 177 links, with 125 connecting to policymakers and 52 to peers. Of 56 faculty members, we identified four knowledge brokers. Six policymakers were identified as key policymakers in the network, too.ConclusionsIt seems that the flow of knowledge produced by research in the health field in Iran is not accomplished well from the producers of research evidence to the users of knowledge. Therefore, it seems necessary to consider incentive and support mechanisms to strengthen the interaction between researchers and policymakers in Iran's health sector.

Communication and Influence of Traditional Culture Based on Social Network Analysis

Social media significantly impacts traditional cultures, yet existing methods struggle to capture the delicate complexities of online cultural discussions. This lack of depth limits understanding of how traditions evolve and adapt in the digital age. To address this, CaCCGAN: Social Culture Analysis, a framework leveraging social network analysis (SNA) is proposed. Content-Aware Cycle-Consistent Generative Adversarial Network (CaCCGAN) explores communication and influence dynamics surrounding traditional culture on social media platforms. CaCCGAN gathers real-time data on traditional culture from Weibo, a prominent Chinese platform, focusing on relevant keywords. By employing Term Frequency-Inverse Document Frequency (TF-IDF) and a Binary Waterwheel Plant Optimization Algorithm (BWPOA), CaCCGAN identifies user-tradition relationships, influential users, and online communities. Furthermore, the CaCCGAN model analyzes communication styles and generates content reflecting these relationships. Analyzing this generated content offers valuable insights for stakeholders interested in cultural preservation, targeted marketing campaigns, and content creation strategies. The proposed CaCCGAN: Social Culture Analysis model attains 25.23%, 21.06% and 55.11% higher Precision value and 29.096%, 41.64% and 33.33% higher F1 Score value compared with the existing method such as PA-BiLSTM Neural Encoding for Cultural Adaptation and Emotion Analysis in Modern Media Communication (PA-BiLSTM), MFCSNet: Modeling Musician-Follower Dynamics in a Complex Social Network to Measure Musical Influence (MFCSNet) and Utilizing Social Media Data Analytics to Integrate Traditional Culture Through Digital Media Interaction and Dissemination (I-RankClus-WOA) respectively. This proposed CaCCGAN: Social Culture Analysis model presents a promising approach to understanding the evolving dynamics of communication and influence surrounding traditional culture online.

Intelligent construction technology based information sharing network for prefabricated building supply chain: a social network analysis approach

PurposeIn the context of Industry 4.0, intelligent construction technologies (ICT) represented by information technology and networking will undoubtedly provide new impetus to the development of the prefabricated building supply chain (PBSC), but they will also bring various potential risks. So far, there is a large lack of research on the comprehensive consideration of the risks associated with the intelligent transformation of PBSC based on the information sharing perspective, and the critical risks and interactions are still unclear, making it difficult to identify efficient risk mitigation strategies. Therefore, this paper aims to reveal the interactions between stakeholders and clarify the critical risk nodes and interactions in information sharing of PBSC (IS-PBSC), and propose targeted risk mitigation strategies.Design/methodology/approachFirstly, this paper creatively delineates the risks and critical stakeholders of IS-PBSC. Secondly, Data is collected through questionnaires to understand the degree of risks impact. Thirdly, with the help of NetMiner 4 software, social network analysis is conducted and IS-PBSC risk network is established to reveal critical risk nodes and interactions. Finally, further targeted discussion of critical risk nodes, the effectiveness and reasonableness of the risk mitigation strategies are proposed and verified through NetMiner 4 software simulation.FindingsThe results show that the critical risks cover the entire process of information sharing, with the lack of information management norms and other information assurance-related risks accounting for the largest proportion. In addition, the government dominates in risk control, followed by other stakeholders. The implementation of risk mitigation strategies is effective, with the overall network density reduced by 41.15% and network cohesion reduced by 24%.Research limitations/implicationsIn the context of Industry 4.0, ICT represented by information technology and networking will undoubtedly provide new impetus to the development of the PBSC, but they will also bring various potential risks. So far, there is a large lack of research on the comprehensive consideration of the risks associated with the intelligent transformation of PBSC based on the information sharing perspective, and the critical risks and interactions are still unclear, making it difficult to identify efficient risk mitigation strategies.Originality/valueBased on the results of risk network visualization analysis, this paper proposes an ICT-based IS-PBSC mechanism that promotes the development of the integration of ICT and PBSC while safeguarding the benefits of various stakeholders.

The hidden strength of small business: Social networks and wet market vendors in China

AbstractThroughout contemporary China, consumers have the option of purchasing food products from “traditional” Chinese wet markets or “modern” supermarket chains. Wet market vendors are economically disadvantaged as the operators of small‐scale businesses with limited investment and high labor costs. Nevertheless, wet market vendors continue to thrive in urban China, despite the continued expansion of supermarket chains. This article combines ethnographic data and social network analysis to examine how social networks provide wet market vendors with some important competitive advantages. The article draws on fourteen months of fieldwork in Sanya City, China, and provides an analysis of the composition, structure, and strength of the network ties of 113 wet market vendors. Vendors tend to have strong and dense ties to individuals who help them establish their businesses. Vendors also rely on strong ties with regular suppliers to help them reduce costs and ensure a regular supply of goods. These strong ties are balanced by weaker ties with a diverse range of customers, including small businesses and household consumers. A combination of both strong and weak network ties contributes to the collective resilience of wet market vendors, allowing them to confront crises, reduce risk and uncertainty, and improve performance.

Mapping the scientific knowledge and approaches to defining and measuring hate crime, hate speech, and hate incidents: A systematic review.

Mapping the scientific knowledge and approaches to defining and measuring hate crime, hate speech, and hate incidents: A systematic review.

Transnational Quaker pacifism and the International Fellowship of Reconciliation. A qualitative case study of two network nodes connecting Finland to Scandinavia and the Anglo‐Saxon world 1919–1961

AbstractIn this article, I will ask, how the international networks of peace movements have influenced the development of Quaker pacifism in Fenno‐Scandinavia. The question is answered with qualitative social network analysis when analyzing the vocational development of two Quaker network nodes, Greta Langenskjöld (1889–1975) and Deryck Sivén (1913–2002). Based on the analysis, I argue that the International Fellowship of Reconciliation provided the most important transnational social network to introduce Quakerism to Fenno‐Scandinavia. Before this, Evangelicalism, Tolstoian Christian anarchism, and Theosophist socialism had molded the ground fitting for the Quaker‐Socialist networks of the IFOR.

FairSNA: Algorithmic Fairness in Social Network Analysis

In recent years, designing fairness-aware methods has received much attention in various domains, including machine learning, natural language processing, and information retrieval. However, in social network analysis (SNA), designing fairness-aware methods for various research problems by considering structural bias and inequalities of large-scale social networks has not received much attention. In this work, we highlight how the structural bias of social networks impacts the fairness of different SNA methods. We further discuss fairness aspects that should be considered while proposing network structure-based solutions for different SNA problems, such as link prediction, influence maximization, centrality ranking, and community detection. This survey-cum-vision clearly highlights that very few works have considered fairness and bias while proposing solutions; even these works are mainly focused on some research topics, such as link prediction, influence maximization, and PageRank. However, fairness has not yet been addressed for other research topics, such as influence blocking and community detection. We review the state of the art for different research topics in SNA, including the considered fairness constraints, their limitations, and our vision. This survey also covers evaluation metrics, available datasets and synthetic network generating models used in such studies. Finally, we highlight various open research directions that require researchers’ attention to bridge the gap between fairness and SNA.

A quality function deployment model by social network and group decision making: Application to product design of e-commerce platforms

Quality function deployment (QFD) is an effective method to convert customer requirements (CRs) into design requirements (DRs) by constructing house of quality (HOQ). With the rapid growth of the e-commerce market, it is a new challenge to utilize the available online reviews to facilitate the implementation of QFD. Therefore, this paper proposes a novel QFD model from the perspective of group decision making (GDM) and social network analysis (SNA), then applies the proposed model to product design under Chinese e-commerce scene. Firstly, this paper extracts CRs from online reviews on e-commerce platforms, and the initial HOQs can be constructed. Then a bilateral negotiation GDM method based on SNA is carried out to generate a consensus-based HOQ, and therefore the final priorities of DRs can be obtained. Finally, a case study is provided to illustrate the applicability, and some discussions and comparative analysis are also conducted. The result indicates that the proposed method can generate effective and stable results for QFD implementation in real-world e-commerce scenario.

Youth and COVID-19 immunization: navigating the nexus of individualism and mistrust

ABSTRACT The objective of this study is to comprehensively examine the diverse discourses among unvaccinated young individuals against COVID-19 in the region of Madrid. Our aim is to gain insights into the motivations and underlying rationales they articulate to justify their decision to remain unvaccinated. To achieve this, we employ a methodological triangulation approach, encompassing in-depth interviews, urban space ethnography, and a social network analysis with a specific focus on Telegram groups. The qualitative data collected is subsequently analyzed using a combination of Grounded Theory procedures and critical discourse analysis. Ultimately, our findings reveal three fundamental discursive dimensions. These encompass the assertion of the right to individual autonomy, perceptions of social and political manipulation, and skepticism towards vaccines rooted in scientific skepticism.

Analysis of network patterns and its influencing factors in Chengdu-Chongqing urban agglomeration based on multi-flow

With the strengthening of the cross-regional flows of the economy, information, innovation, and population, this paper constructs a network model of multi-flow integration and analyzes the spatial pattern and influencing factors of urban networks in Chengdu-Chongqing Urban Agglomeration using social network analysis and spatial analysis technology. The main conclusions are as follows. (1) The density and efficiency are in the transition stage from the primary level to the medium level in the comprehensive network. (2) The overall pattern keeps a polyhedral pyramid structure with Chengdu ↔ Chongqing as the core axis, and the grade of each axis has been significantly raised. (3) Four groups are formed using the social network method and show a geographic proximity effect. In addition, the connections within each group are relatively close, but the connections between the groups are significantly different. (4) Location conditions, economic development level, enterprise development level, scientific research investment, scientific and technological development level, and government support have a greater impact on the formation of the comprehensive network of Chengdu-Chongqing urban agglomeration. Information application level and transportation accessibility show a small impact and human capital level has not yet produced a significant impact.

Towards sustainable manufacturing: A comprehensive analysis of circular economy key performance indicators in the manufacturing industry

In the pursuit of sustainable development, the concept of Circular Economy (CE) has emerged as a transformative alternative to the traditional linear economic model characterized by take, make, use, and dispose practices. However, there is a growing recognition of the limitations of the linear economy in addressing contemporary global challenges, leading to a pressing need for a more regenerative approach. This study aims to explore and analyze Key Performance Indicators (KPIs) associated with the circular economy, particularly focusing on the manufacturing industry, to provide a valuable guide for enterprises looking to integrate CE principles effectively and reinforce sustainability. The novelty of this study lies in its comprehensive examination of KPIs that embrace sustainability's triple bottom lines - environmental, economic, and social dimensions. The systematic selection of relevant KPIs and the utilization of Social Network Analysis (SNA) to identify the most influential CE KPIs within the manufacturing industry add depth to the research. By identifying and upgrading significant KPIs representing various facets of CE development, this study contributes to a more meticulous understanding of how enterprises can measure their progress towards circularity. In each of the triple bottom lines of sustainability, five significant KPIs were recognized and upgraded to the second assessment process, where these 15 KPIs are analyzed using SNA to obtain 5 aggregated KPIs. The comprehensive analysis of the obtained fifteen KPIs culminates in aggregated CE indicators, primarily strategies and initiatives (SI), material efficiency (ME), productivity of remanufacturing (OR), technology investment (ROR), and eco-innovation (EI). The aggregated Key Performance Indicators (KPIs) displayed an extreme value of the weighted average index attributed to strategies and initiatives KPI with a value of 0.067. These aggregated KPIs provide a practical framework for manufacturers to assess and optimize their circular economy practices. It's essential to note that all binary values incorporated in the proposed approach are derived from an extensive literature review. These values may vary depending on the specific objectives of individual manufacturing firms or focus groups. As a result, the proposed approach is adaptable to diverse manufacturing industries, allowing customization to suit the unique input criteria of each firm or group. Significantly, the current work emphasizes the influential role of manufacturers in shaping a sustainable future in alignment with development goals.

Research on the Evolution of the Spatial Association Network Structure and Driving Factors of China’s Agricultural Green Development

Against the backdrop of global environmental challenges and sustainable development goals, this paper pioneers the application of social network analysis to the study of spatial associations in China’s agricultural green development. It not only enhances the understanding of the spatial interconnectivity and network structural characteristics of agricultural green developments, but also captures the complex dependencies and interactions among provinces through a network lens, offering a fresh perspective on regional agricultural cooperation and competition. The study reveals: (1) The spatial network of China’s agricultural green development displays strong overall connectivity and enhanced stability, with regional green development trends becoming increasingly interlinked and interdependent. (2) The network exhibits a clear hierarchical and core-periphery structure which, over time, shows signs of diminishing, indicating a narrowing of developmental disparities among regions. (3) Significant shifts in the roles and positions of provinces within the network occur due to the relocation of industrial focal points and adjustments in development strategies, highlighting the complexity of dynamic changes among regions. (4) The spatial association network can be divided into four main clusters: Net spillover block, Bidirectional spillover block, Net beneficial block, and Broker block, with significant gradient characteristics in the relationships between these clusters, suggesting directional and differential flows and exchanges of resources and information among regions. (5) Geographic proximity, economic development level, informatization, and agricultural technological advancement significantly influenced the development and structural evolution of the network.

Is corrections officers' use of illegal force networked? Network structure, brokerage, and key players in the New York City Department of Correction

PurposeRecent research on police misconduct has adopted a network perspective, while recent work on correctional officer (CO) use of force has similarly framed it as an organizational behavior, learned through socialization and deployed with considerable discretion. This paper leverages the network paradigm in police misconduct research to study the use of force by COs. MethodsUsing data on lawsuits involving the New York City Department of Correction from 2013 to 2022, this paper forms a co-offending network of those COs who have been sued for excessive force. This paper then uses descriptive social network analysis and key player selection and community detection methods. ResultsAfter describing the basic network structure of COs who use force together, this paper identifies brokers who connect disparate parts of the CO network; it also uses a community detection algorithm to identify clusters of COs involved in force incidents. Finally, the paper compares this network to an analogous network of police use of force, finding structural similarities. ConclusionsThis analysis bridges disparate work on correctional officer use of force and police misconduct; for policymakers who seek to curtail COs' excessive use of force, this paper might provide a blueprint for identifying key players and clusters.

Attributes and Predictors of Opinion Leaders on Twitter: COVID-19 Childhood Vaccination Campaign

ABSTRACT Identifying attributes of the COVID-19 childhood vaccine message disseminators is beneficial to health campaign research. This study examines the We Can Do This COVID-19 childhood vaccination health campaign message disseminators on Twitter during 2021–2022. Guided by the diffusion of innovation theory and the theory of the two-step flow communication, we classify the disseminators (n=823) and examine their influence over the two-year period. A manual content analysis and social network analysis were conducted to measure the impact of disseminators on their networks through in-degree centrality assessment. Results revealed that experts in medical fields, industrial professionals, and social media influencers were the top three most common career titles disclosed in Twitter bios among individual accounts, whereas local nonprofit organizations, governments, and companies were the most common organizational accounts. Mann-Whitney U Tests indicated that in both years message disseminators with clinical medicine expertise were more influential than those who did not reveal such expertise. However, only in 2021 were campaign message disseminators with parental expertise more influential within the social network. We discuss the implications of disseminator classification as well as the significance of enhancing health campaigns by identifying who discusses them on social media.

Simulation of Communication Paths with Social Network Analysis as the Core and CAD Collaborative Visualization

Simulation of Communication Paths with Social Network Analysis as the Core and CAD Collaborative Visualization

Using Deep Learning Approaches to Quantify Landscape Preference of the Chinese Grand Canal: An Empirical Case Study of the Yangzhou Ancient Canal

Landscape preference emerges from the dynamic interaction between individuals and their environment and plays a pivotal role in the preservation and enhancement of the Chinese Grand Canal’s scenery. As a vast linear heritage, employing conventional methods for analyzing landscape preferences can be resource-intensive in terms of both time and labor. Amid the rapid advancement of Big Data and Artificial Intelligence (AI), a cognitive framework for understanding the Chinese Grand Canal’s landscape preferences has been developed, encompassing two primary aspects: the characteristic features of landscape preference and its spatial organization. Geotagged photographs from tourism media platforms focused on the Yangzhou Ancient Canal were utilized, and the EasyDL deep learning platform was employed to devise a model. This model assesses current landscape preferences through an analysis of photographic content, element composition patterns, and geospatial distribution, integrating social network and point density analyses. Our findings reveal that the fusion of Yangzhou Ancient Canal and classical gardens creates a sought-after ‘Canal and Watercraft Remains’ landscape. Tourists’ preferences for different landscape types are reflected in the way the elements are combined in the photographs. Overall, landscape preferences are dense in the north and sparse in the south. Differences in tourists’ perceptions of the value of and preferences for heritage sites lead to significant variations in tourist arrivals at different sites. This approach demonstrates efficiency and scalability in evaluating the Chinese Grand Canal landscape, offering valuable insights for its strategic planning and conservation efforts.

Spatial Network Analysis of Coupling Coordination between Digital Financial Inclusion and Common Prosperity in the Yangtze River Delta Urban Agglomeration

Digital financial inclusion and common prosperity are pivotal elements in promoting the sustainable socioeconomic development of China. This study introduces a novel Multi-Criteria Decision Analysis (MCDA) method to evaluate the Common Prosperity Index (CPI). Using this index, alongside the Digital Financial Inclusion Index (DFII) released by Peking University, it examines the evolution of the coupling coordination relationship between digital financial inclusion and common prosperity within the Yangtze River Delta (YRD) urban agglomeration from 2011 to 2021. By integrating gravity models and social network analysis, in this paper, we thoroughly investigate the spatiotemporal evolution characteristics of the spatial network of this coupling coordination relationship. The results indicate that both the DFII and CPI generally exhibit an upward trend, but the decline in the coupling degree reflects a weakened interaction strength between them. Specifically, Anhui significantly lags behind Jiangsu, Zhejiang, and Shanghai in the development of digital financial inclusion and common prosperity, indicating regional development imbalances. Furthermore, the strength of spatial connections in city coupling coordination has significantly increased, with Nanjing’s siphon effect on cities in Anhui becoming markedly stronger, and the number of core cities in the network increasing, which demonstrates a geographical proximity feature in network development. Additionally, the overall network characteristics are transitioning towards higher density and “small-world” properties, suggesting a trend toward network stabilization. The disparity in centrality among cities has decreased, with an overall enhancement in centrality, where the spatial spillover effects from core areas such as Hangzhou-Ningbo, Nanjing-Changzhou, and Shanghai-Suzhou-Wuxi significantly promote the development of peripheral cities. Based on these findings, this paper proposes policy recommendations for the sustainable development of digital financial inclusion and common prosperity in the YRD region.

Social Network Analysis of Farmers after the Private Cooperatives’ “Intervention” in a Rural Area of China—A Case Study of the XiangX Cooperative in Shandong Province

In China, private-owned cooperatives are becoming increasingly involved in agricultural production. In order to find the key characteristics of smallholders’ social networks after the appearance of cooperatives and better organize different farmland operators, this study completed a field survey of 114 smallholders who adopted farmland trusteeship service of a private-owned cooperative in China and applied the social network analysis to reveal the following results. (1) Compared to the theoretical ideal value, smallholders’ social networks showed low network density, efficiency, and little relevancy. (2) In the social network of mechanical-sharing, neighbor, kinship, and labor-sharing relationships, some isolated nodes existed, but no isolated nodes are found in the synthetic network. (3) The mechanical-sharing relationship among smallholders was stronger than the other relationships. (4) Machinery owners, farmers whose plots are on the geometric center and experienced older farmers showed higher centralities in the network, but village cadres did not. (5) The centralities and QAP correlation coefficients among different networks inside the cooperative were lower than that inside a single village. As a result, this paper confirmed that the ability of cooperatives to organize farmers’ social networks is not ideal. Farmers’ trust of farmland to a cross-village cooperatives does not help them to form a larger social network than their villages. In the future, the answer to the question of “who will farm the land” will still lie with the professional farmers and highly autonomous cooperatives.